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Global exponential stability of delayed fuzzy cellular neural networks with Markovian jumping parameters

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Abstract

This paper deals with the global exponential stability in the mean square of fuzzy cellular neural networks with time-varying delays and Markovian jumping parameters. By constructing suitable Lyapunov functionals, we obtain several sufficient conditions which can be expressed in terms of linear matrix inequalities (LMIs). The proposed LMI results are computationally efficient as it can be solved numerically by using Matlab LMI toolbox. An example is given to show the effectiveness of the results.

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Acknowledgments

The authors would like to thank the Editor and the anonymous referees for their very valuable comments and helpful suggestions, which have been very useful for improving this work. This research is supported by the Youth Science Foundation of Shanxi Province (2010021001-2), the National Sciences Foundation of China (10901145), the Top Young Academic Leaders of Higher Learning Institutions of Shanxi, the National Natural Science Foundation of China (under Grant No. 60771026 and No. 10771199), the Programme for New Century Excellent Talents in University (NCET050271), and the Special Scientific Research Foundation for the Subjects of Doctors in University (20060110005).

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Authors and Affiliations

  1. Department of Mathematics, North University of China, Taiyuan, Shanxi, 030051, China

    Wei Han

  2. Department of Mathematics and Physics, Hebei Normal University of Science and Technology, Qinhuangdao, Hebei, 066004, China

    Yan Liu

  3. Department of Mathematics, Ocean University of China, Qingdao, Shandong, 266071, China

    Linshan Wang

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  1. Wei Han
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  2. Yan Liu
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  3. Linshan Wang
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Correspondence to Wei Han.

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Han, W., Liu, Y. & Wang, L. Global exponential stability of delayed fuzzy cellular neural networks with Markovian jumping parameters. Neural Comput & Applic 21, 67–72 (2012). https://doi.org/10.1007/s00521-011-0685-4

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  • DOI: https://doi.org/10.1007/s00521-011-0685-4

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